Senior Agentic AI Engineer
Alternative Path Private Limited
リモート勤務
- 勤務地
- Remote (United States)
- 勤務時間
- Full Time
- 掲載日
- 2026年10月14日
応募する前に、企業のウェブサイトで現在も募集中かどうかと詳しい条件を確認してください。
仕事内容
操作画面は日本語です。企業が掲載した求人の職種名や説明文は原文のまま表示され、英語の場合があります。
This is a remote position.
Senior AI & Agentic System Engineer
Experience:5+ Years
Location:Gurgaon, India / Fully Remote
Team:AI Platform / EngineeringAbout the Role
We are looking for aSenior AI & Agentic System Engineerto design and build production-grade AI agents that can reason, use tools, interact with APIs, and execute complex multi-step workflows.
You’ll work at the intersection ofLLM engineering, agent architecture, backend systems, and cloud infrastructure, with significant ownership over architecture, reliability, evaluation, and scalability.
Requirements
Key Responsibilities
Design and build autonomous AI agents capable of tool use, web/API interaction, memory, and multi-step task execution.
Architect agentic workflows includingplanner/executor/verifier, multi-agent, HITL, retry, and failure-recovery patterns.
Integrate LLM providers such asOpenAI, Anthropic, and Gemini, including structured outputs, function calling, context management, and prompt optimization.
BuildRAG and knowledge pipelinesusing embeddings, vector databases, hybrid search, reranking, and agent memory.
Develop scalable backend services usingPython and/or Node.js/TypeScript, REST/GraphQL APIs, async processing, and background jobs.
Design reliable distributed systems with appropriate patterns for state persistence, caching, idempotency, event-driven workflows, and fault tolerance.
Build observability and evaluation frameworks for AI systems, including tracing, behavioral regression testing, latency, quality, and token-cost monitoring.
Own CI/CD and cloud deployments across development, staging, and production environments.
Evaluate emerging technologies such asMCP, A2A, reasoning models, and agent frameworksand recommend practical adoption.
Required Skills
5+ years of software/backend engineering experience with strong system-design expertise.
Hands-on experience buildingproduction AI agents, beyond basic chatbot implementations.
Strong experience with at least one major LLM provider SDK:OpenAI, Anthropic, or Gemini.
Strong understanding ofprompt engineering, tool/function calling, structured outputs, context management, and token optimization.
Experience with agent frameworks/patterns such asLangGraph, CrewAI, AutoGen, ReAct, or plan-and-execute.
StrongPython and/or Node.js/TypeScriptdevelopment skills.
Experience withRAG, embeddings, vector databases, hybrid retrieval, and reranking.
Strong knowledge ofREST/GraphQL APIs, asynchronous processing, databases, and distributed systems.
Hands-on AWS experience, particularlyLambda, ECS/Fargate, API Gateway, S3, SQS, SNS/EventBridge, IAM, and CloudWatch.
Experience withDocker, GitHub Actions, and Terraform.
Understanding of AI security, includingprompt injection, guardrails, output validation, and safe tool execution.
AI/LLMOps & Evaluation
Experience with tools such as:
Langfuse, LangSmith, Helicone, or Arize Phoenix
RAGAS, DeepEval, Promptfoo, or Braintrust
LLM tracing, behavioral evaluations, regression testing, and cost monitoring.
Nice to Have
Browser automation usingPlaywright or Puppeteer.
Experience with multimodal/vision-based agents.
Knowledge ofGraphRAG and knowledge graphs.
Experience withTemporal or durable workflow execution.
Open-source contributions to AI tooling.
Background in ML/data science alongside software engineering.
Tech Stack
LLMs:OpenAI, Anthropic Claude
Agent Infrastructure:Custom orchestration, MCP
Backend:Python, Node.js/TypeScript
Cloud:AWS Lambda, ECS/Fargate
Data:PostgreSQL, S3, SQS, DynamoDB
CI/CD:GitHub Actions
Observability:Datadog, CloudWatch, Langfuse
IaC:Terraform
Browser Automation:Playwright
Originally posted on Himalayas